Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects potential Adversary-in-the-Middle (AiTM) activity by identifying a pattern where a successful multi-factor authentication sign-in event is quickly followed by another successful sign-in for the same user from a different IP address, device, or geographic location. This behavior is indicative of session cookie theft and replay, commonly associated with phishing toolkits like Evilginx or NovaCookies.
Detects potential Adversary-in-the-Middle (AiTM) session token replay attacks where a user successfully authenticates with MFA and is followed shortly by a subsequent successful login for the same user from a different IP address or device without a fresh MFA challenge, suggesting the use of a stolen session cookie.
This rule detects potential account hijacking via OAuth device-code authorization flow, specifically identifying patterns associated with phishing kits (e.g., EvilTokens, ARToken). It monitors sign-in events where the device code flow is utilized, specifically flagging successful grants that potentially bypass standard interactive credential prompts.
Detects potential session hijacking where a user logs into Google Workspace from a new IP or country, followed within an hour by the registration of a new security key or passkey, which is a common technique to establish persistent unauthorized access.
Detects a sequence of events where a user performs a device-code authentication followed rapidly by a device enrollment, and subsequently continues to access cloud services (Microsoft Graph, Exchange Online, Intune) shortly after their account password has been reset. This pattern is indicative of persistent access maintained via a registered device or OAuth token that survives credential remediation.
Detects the 'GhostCode' attack pattern where an adversary acquires a Primary Refresh Token (PRT) shortly after a successful OAuth device code authentication. This correlation identifies potential session hijacking or token theft resulting from an adversary-controlled device registration.
Detects a suspicious authentication pattern involving 3 or more MFA failures within 15 minutes, immediately followed by an MFA success for the same user. This pattern is characteristic of potential Adversary-in-the-Middle (AiTM) activity, where an attacker intercepts a session or MFA token and relays it through separate infrastructure, while the legitimate user's own MFA attempts fail or time out.
Detects Azure AD/Entra ID authentication events where a session token or cookie is used without performing a fresh interactive MFA challenge, which is characteristic of session hijacking or adversary-in-the-middle (AiTM) relay attacks (e.g., NovaCookies) used to bypass security controls after initial authentication.
Detects Microsoft 365 sign-in events where MFA was successfully satisfied, but the sign-in is simultaneously flagged by risk detection engines as exhibiting anomalous token or session characteristics, indicative of Adversary-in-the-Middle (AiTM) session hijacking.
Detects the enrollment of a new security key or passkey shortly after an unfamiliar or suspicious sign-in event within Google Workspace. This behavior is indicative of an adversary establishing persistent access following a successful session hijack or credential phishing campaign, specifically targeting authentication mechanisms to bypass existing security controls.
Detects anomalous Entra ID sign-in patterns characterized by a single session ID replayed from multiple diverse source IP addresses and Autonomous System Numbers (ASNs) within a short timeframe. This behavior is indicative of Session Hijacking (AiTM/Adversary-in-the-Middle) where an attacker maintains persistence by proxying requests through a residential network to bypass conditional access policies and evade location-based threat detection.
Detects session hijacking (AiTM) attempts where a failed or interrupted sign-in (ResultType 50199) is followed by a successful login using the same SessionId but with an Axios user-agent, indicating automated replay of a stolen session token rather than legitimate browser usage.
Detects potentially malicious OAuth device code sign-ins by identifying sign-in events that exhibit anomalous characteristics, such as atypical geographic locations, rare client-application combinations, unmanaged/noncompliant device status, or elevated risk signals associated with the account. This detection helps identify account compromise or malicious OAuth consent activity often associated with 'EvilTokens' or device-code phishing attacks.
Detects potentially malicious OAuth device code sign-ins by identifying sign-in events that exhibit anomalous characteristics, such as atypical geographic locations, rare client-application combinations, unmanaged/noncompliant device status, or elevated risk signals associated with the account. This detection helps identify account compromise or malicious OAuth consent activity often associated with 'EvilTokens' or device-code phishing attacks.
Detects potential abuse of stolen OAuth session tokens, where refresh tokens are used to authenticate after a user has performed a password reset. This rule identifies accounts that continue to sign in from previously unseen devices or IP addresses within 24 hours post-password reset, a technique consistent with session persistence mechanisms used by adversary tools and platforms like EvilTokens.
Detects anomalous outbound email activity from an account that recently performed an OAuth device code sign-in characterized by elevated risk levels. The rule identifies potential token abuse by looking for a high volume of emails with either a significant percentage of external recipients or patterns indicative of bulk mailing, common in phishing campaigns that leverage compromised identities (e.g., EvilTokens).
Detects sign-in events where Multi-Factor Authentication (MFA) was satisfied using an External Authentication Method (EAM) that asserts specific possession or inherence claims (e.g., 'hwk' - hardware key). This behavior may indicate an adversary attempting to bypass or forge MFA responses via a rogue EAM provider.
This rule detects persistence by identifying accounts that continue to authenticate using an External Authentication Method (EAM) both before and after a password reset event. This behavior suggests that an adversary has established a persistent authentication mechanism (such as an EAM) that survives a standard password reset, indicating potential account compromise and bypass of primary authentication controls.
Detects successful authentication events for accounts that have been dormant for at least 90 days, correlated with suspicious activity markers such as recent failed sign-in attempts, access from an unfamiliar geographic location or ASN, or a complete absence of historical sign-in activity.
Detects successful authentication events for accounts that have been dormant for at least 90 days, correlated with suspicious activity markers such as recent failed sign-in attempts, access from an unfamiliar geographic location or ASN, or a complete absence of historical sign-in activity.
Detects patterns associated with the TeamFiltration backdoor module, specifically unauthorized OneDrive/SharePoint file modifications occurring shortly after an authentication from a previously unseen device/IP. The rule flags file changes (modifications, deletions, or renames) involving potential executable or script extensions, or those performed by the OneDrive SyncEngine app from a new source.
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